Multiobjective job shop scheduling using rule-coded genetic local search

The multiobjective job shop scheduling problem with mean tardiness and the maximum tardiness as the objectives is addressed. A genetic local search algorithm is proposed with several features. First, it uses a dispatching rule-based genome encoding scheme, and the encoded dispatching rules are chosen carefully. Second, its mating selection mechanism combines the advantages of two representative ones in the literature. Third, it enhances a recently proposed population-based local search procedure. The benefits of the proposed idea are verified through experiments on a public benchmark problem set. In the experiments, the proposed algorithm is also shown to significantly outperform a recent algorithm specific to the multiobjective job shop scheduling problem.